Stochastic Agent-based Modeling of Angiogenesis and Tissue Growth

Illinois Institute Of Technology, Chicago IL

Investigators

Abstract

0731201 Cinar This project will combine in vitro and in vivo (animal model) experimental studies in order to develop new models for angiogenesis in engineered tissues. The research results will contribute to the knowledge base in simulation-based engineering science and in dynamic modeling of stochastic complex biomedical systems. In addition, knowledge acquired in this research will provide important insight into mechanism governing angiogenesis in engineered tissues. The outcome of the research will be new strategies, methods, and tools: (1) To develop multi-scale, agent-based predictive models for conducting in silico experiments and optimize values of factors for angiogenesis and tissue growth; (2) To assess the impact of stochastic effects on the dynamics of angiogenesis and tissue growth, and conduct sensitivity analysis; and (3) To develop in vitro and in vivo experimental techniques to validate model predictions and therapy protocols. Mathematical models that can predict the rate and extent of angiogenesis in engineered tissues based on soluble and physical factors will reduce guesswork in tissue engineering therapy and ultimately enable the selection of the best tissue growth conditions for a specific individual and tissue or organ. The proposed activity also contributes to promoting education and training in modeling of complex dynamic stochastic systems, hierarchical agent-based models, and angiogenesis and tissue engineering. Furthermore, the techniques for model development and assessment of the effects of stochastic variations can be used in complex adaptive systems in many fields central to national and global concerns. Significant effort will be devoted to disseminate research results in the form of software, case studies, and practical training to researchers and graduate students, K-12 teachers, undergraduate students and students from underrepresented groups in science and engineering.